Articles producció científica> Enginyeria Informàtica i Matemàtiques

Pattern formation and bifurcation analysis of delay induced fractional-order epidemic spreading on networks

  • Dades identificatives

    Identificador: imarina:9326007
    Autors:
    Zhou, JiayingYe, YongArenas, AlexGomez, SergioZhao, Yi
    Resum:
    The spontaneous emergence of ordered structures, known as Turing patterns, in complex networks is a phenomenon that holds potential applications across diverse scientific fields, including biology, chemistry, and physics. Here, we present a novel delayed fractional-order susceptible–infected–recovered–susceptible (SIRS) reaction–diffusion model functioning on a network, which is typically used to simulate disease transmission but can also model rumor propagation in social contexts. Our theoretical analysis establishes the Turing instability resulting from delay, and we support our conclusions through numerical experiments. We identify the unique impacts of delay, average network degree, and diffusion rate on pattern formation. The primary outcomes of our study are: (i) Delays cause system instability, mainly evidenced by periodic temporal fluctuations; (ii) The average network degree produces periodic oscillatory states in uneven spatial distributions; (iii) The combined influence of diffusion rate and delay results in irregular oscillations in both time and space. However, we also find that fractional-order can suppress the formation of spatiotemporal patterns. These findings are crucial for comprehending the impact of network structure on the dynamics of fractional-order systems.
  • Altres:

    Autor segons l'article: Zhou, Jiaying; Ye, Yong; Arenas, Alex; Gomez, Sergio; Zhao, Yi
    Departament: Enginyeria Informàtica i Matemàtiques
    Autor/s de la URV: Arenas Moreno, Alejandro / Gómez Jiménez, Sergio
    Paraules clau: Time-fractional order Spatiotemporal pattern Delay Average degree
    Resum: The spontaneous emergence of ordered structures, known as Turing patterns, in complex networks is a phenomenon that holds potential applications across diverse scientific fields, including biology, chemistry, and physics. Here, we present a novel delayed fractional-order susceptible–infected–recovered–susceptible (SIRS) reaction–diffusion model functioning on a network, which is typically used to simulate disease transmission but can also model rumor propagation in social contexts. Our theoretical analysis establishes the Turing instability resulting from delay, and we support our conclusions through numerical experiments. We identify the unique impacts of delay, average network degree, and diffusion rate on pattern formation. The primary outcomes of our study are: (i) Delays cause system instability, mainly evidenced by periodic temporal fluctuations; (ii) The average network degree produces periodic oscillatory states in uneven spatial distributions; (iii) The combined influence of diffusion rate and delay results in irregular oscillations in both time and space. However, we also find that fractional-order can suppress the formation of spatiotemporal patterns. These findings are crucial for comprehending the impact of network structure on the dynamics of fractional-order systems.
    Àrees temàtiques: Statistical and nonlinear physics Química Physics, multidisciplinary Physics, mathematical Physics and astronomy (miscellaneous) Physics and astronomy (all) Physics Mathematics, interdisciplinary applications Mathematics, applied Mathematics (miscellaneous) Mathematics (all) Mathematical physics Materiais Matemática / probabilidade e estatística Interdisciplinar Geociências General physics and astronomy General mathematics Engenharias iv Engenharias iii Engenharias ii Engenharias i Economia Direito Ciências biológicas ii Ciências biológicas i Ciência da computação Astronomia / física Applied mathematics
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    Adreça de correu electrònic de l'autor: sergio.gomez@urv.cat alexandre.arenas@urv.cat
    Identificador de l'autor: 0000-0003-1820-0062 0000-0003-0937-0334
    Data d'alta del registre: 2024-09-28
    Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
    Enllaç font original: https://www.sciencedirect.com/science/article/pii/S0960077923007063
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Chaos Solitons & Fractals. 174 113805-
    Referència de l'ítem segons les normes APA: Zhou, Jiaying; Ye, Yong; Arenas, Alex; Gomez, Sergio; Zhao, Yi (2023). Pattern formation and bifurcation analysis of delay induced fractional-order epidemic spreading on networks. Chaos Solitons & Fractals, 174(), 113805-. DOI: 10.1016/j.chaos.2023.113805
    DOI de l'article: 10.1016/j.chaos.2023.113805
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2023
    Tipus de publicació: Journal Publications
  • Paraules clau:

    Applied Mathematics,Mathematical Physics,Mathematics (Miscellaneous),Mathematics, Applied,Mathematics, Interdisciplinary Applications,Physics,Physics and Astronomy (Miscellaneous),Physics, Mathematical,Physics, Multidisciplinary,Statistical and Nonlinear Physics
    Time-fractional order
    Spatiotemporal pattern
    Delay
    Average degree
    Statistical and nonlinear physics
    Química
    Physics, multidisciplinary
    Physics, mathematical
    Physics and astronomy (miscellaneous)
    Physics and astronomy (all)
    Physics
    Mathematics, interdisciplinary applications
    Mathematics, applied
    Mathematics (miscellaneous)
    Mathematics (all)
    Mathematical physics
    Materiais
    Matemática / probabilidade e estatística
    Interdisciplinar
    Geociências
    General physics and astronomy
    General mathematics
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Engenharias i
    Economia
    Direito
    Ciências biológicas ii
    Ciências biológicas i
    Ciência da computação
    Astronomia / física
    Applied mathematics
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